Anti-collision and motion monitoring, control, and alerting systems and methods

ABSTRACT

Systems and methods presented herein include an anti-collision and motion monitoring system includes light detection and ranging (LiDAR) systems configured to detect locations of objects in an environment. The anti-collision and motion monitoring system also includes camera systems configured to capture images of the objects in the environment that are detected by the LiDAR systems. The anti-collision and motion monitoring system further includes processing circuitry configured to coordinate operation of the LiDAR systems and the camera systems, to receive inputs from the LiDAR systems and the camera systems relating to the objects in the environment, to process the inputs received from the LiDAR systems and the camera systems to determine outputs relating to monitoring, control, and alerting relating to the objects in the environment, and to communicate the outputs to a central coordinator.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims priority to and the benefit of U.S. ProvisionalApplication No. 62/859,533, entitled “Anti-Collision and Motion ControlSystems and Methods,” filed Jun. 10, 2019, and claims priority to andthe benefit of U.S. Provisional Application No. 62/994,522, entitled“Anti-Collision and Motion Monitoring, Control, and Alerting Systems andMethods,” filed Mar. 25, 2020, both of which are hereby incorporated byreference in their entireties for all purposes.

FIELD OF DISCLOSURE

The present disclosure relates generally to anti-collision and motioncontrol alerting systems and methods. More specifically, embodiments ofthe present disclosure relate to systems and methods for anti-collisionand motion control using light detection and ranging (LiDAR) andhigh-fidelity camera techniques to provide alerts relating to activityin a physical environment.

BRIEF DESCRIPTION

Certain embodiments commensurate in scope with the originally claimedsubject matter are summarized below. These embodiments are not intendedto limit the scope of the claimed subject matter, but rather theseembodiments are intended only to provide a brief summary of possibleforms of the subject matter. Indeed, the subject matter may encompass avariety of forms that may be similar to or different from theembodiments set forth below.

In certain embodiments, an anti-collision and motion control systemincludes a plurality of anti-collision and motion monitoring systems.Each anti-collision and motion monitoring system includes one or morelight detection and ranging (LiDAR) systems configured to detectlocations of one or more objects in an environment, one or more camerasystems configured to capture images of the one or more objects in theenvironment that are detected by the one or more LiDAR systems, andprocessing circuitry configured to receive inputs from the one or moreLiDAR systems and the one or more camera systems relating to the one ormore objects in the environment, and to process the inputs received fromthe one or more LiDAR systems and the one or more camera systems todetermine outputs relating to the one or more objects in theenvironment. The anti-collision and motion control system also includesa central coordinator configured to receive the outputs from theprocessing circuitry of the plurality of anti-collision and motionmonitoring systems, to compile the outputs into visualization datarelative to a plurality of grid sections of a rectilinear grid of theenvironment, and to communicate a visualization of the rectilinear gridof the environment to a user interface. The visualization includes thevisualization data relative to the plurality of grid sections of therectilinear grid of the environment. In addition, the visualization datadefines positioning and movement of the one or more objects relative tothe plurality of grid sections of the rectilinear grid of theenvironment.

In addition, in certain embodiments, an anti-collision and motionmonitoring system includes one or more light detection and ranging(LiDAR) systems configured to detect locations of one or more objects inan environment and one or more camera systems configured to captureimages of the one or more objects in the environment that are detectedby the one or more LiDAR systems. The anti-collision and motionmonitoring system also includes processing circuitry configured toreceive inputs from the one or more LiDAR systems and the one or morecamera systems relating to the one or more objects in the environment,to process the inputs received from the one or more LiDAR systems andthe one or more camera systems to determine primary data relating to theone or more objects in the environment relative to a first plurality ofgrid sections of a rectilinear grid of the environment, and to requestcomplementary data relating to the one or more objects in theenvironment relative to a second plurality of grid sections of therectilinear grid from a second anti-collision and motion monitoringsystem only when the processing circuitry cannot determine primary datarelating to the one or more objects in the environment relative to thesecond plurality of grid sections of the rectilinear grid.

In addition, in certain embodiments, an anti-collision and motioncontrol system, includes one or more anti-collision and motionmonitoring systems. Each anti-collision and motion monitoring systemincludes one or more light detection and ranging (LiDAR) systemsconfigured to detect locations of one or more objects in an environment,one or more camera systems configured to capture images of the one ormore objects in the environment that are detected by the one or moreLiDAR systems, and processing circuitry configured to receive inputsfrom the one or more LiDAR systems and the one or more camera systemsrelating to the one or more objects in the environment, and to processthe inputs received from the one or more LiDAR systems and the one ormore camera systems to determine outputs relating to the one or moreobjects in the environment. The anti-collision and motion control systemalso includes a central coordinator configured to receive the outputsfrom the processing circuitry of the one or more anti-collision andmotion monitoring systems, to determine one or more alarms relating toactivity of the one or more objects in the environment based at least inpart on the outputs received from the processing circuitry of the one ormore anti-collision and motion monitoring systems, and to communicatethe one or more alarms to one or more wearable devices located in theenvironment.

Various refinements of the features noted above may be undertaken inrelation to various aspects of the present disclosure. Further featuresmay also be incorporated in these various aspects as well. Theserefinements and additional features may exist individually or in anycombination.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presentdisclosure will become better understood when the following detaileddescription is read with reference to the accompanying drawings in whichlike characters represent like parts throughout the drawings, wherein:

FIG. 1 is a schematic diagram of an anti-collision and motion controlsystem using light detection and ranging (LiDAR) and high-fidelitycamera techniques, in accordance with embodiments the presentdisclosure;

FIG. 2 is a perspective view of a physical environment that may bemonitored by the anti-collision and motion control system of FIG. 1 , inaccordance with embodiments the present disclosure;

FIG. 3 are perspective views of a plurality of anti-collision and motionmonitoring devices of the anti-collision and motion control system ofFIG. 1 , in accordance with embodiments the present disclosure;

FIG. 4 is a schematic diagram of processing circuitry of theanti-collision and motion monitoring devices, in accordance withembodiments the present disclosure;

FIG. 5 is a schematic diagram of control circuitry of the centralcoordinator, in accordance with embodiments the present disclosure;

FIG. 6 is a simplified example of a rectilinear grid representing aphysical environment that may be monitored by one or more anti-collisionand motion monitoring devices, in accordance with embodiments thepresent disclosure;

FIG. 7 illustrates another view of the rectilinear grid of FIG. 6 , inaccordance with embodiments the present disclosure; and

FIGS. 8-11 illustrate a plurality of views that may be displayed via auser interface, in accordance with embodiments the present disclosure.

DETAILED DESCRIPTION

One or more specific embodiments of the present disclosure will bedescribed below. In an effort to provide a concise description of theseembodiments, all features of an actual implementation may not bedescribed in the specification. It should be appreciated that in thedevelopment of any such actual implementation, as in any engineering ordesign project, numerous implementation-specific decisions must be madeto achieve the developers' specific goals, such as compliance withsystem-related and business-related constraints, which may vary from oneimplementation to another. Moreover, it should be appreciated that sucha development effort might be complex and time consuming, but wouldnevertheless be a routine undertaking of design, fabrication, andmanufacture for those of ordinary skill having the benefit of thisdisclosure. Further, to the extent that certain terms such as parallel,perpendicular, and so forth are used herein, it should be understoodthat these terms allow for certain deviations from a strict mathematicaldefinition, for example to allow for deviations associated withmanufacturing imperfections and associated tolerances.

The anti-collision and motion control system described herein includesfully packaged anti-collision and motion monitoring devices that utilizesoftware algorithms to monitor critical areas within physicalenvironments, and accurately identify and protecting a plurality ofdifferent types of objects (e.g., machinery and/or people), whetherautonomous or non-autonomous, located within designated areas within thephysical environments. In doing so, the anti-collision and motioncontrol system described herein is capable of, for example, triggeringalarms, alerting operators, and setting areas within the physicalenvironment to controlled states through communication within equipmentlocated within the physical environment. Using a three-dimensionalmapping of the physical environment, the anti-collision and motionmonitoring devices are capable of accurately identifying particularobjects (e.g., humans, vehicles, pieces of equipment, and so forth),providing a two-step recognition process using light detection andranging (LiDAR) modules and high-fidelity camera modules, and makingdecisions according to the particular object's proximity to an area ofparticular interest within the physical environment. For example, if adetermination is made that a human is too close to the area ofparticular interest, the anti-collision and motion control system maycontrol operating parameters of certain pieces of equipment in the areaof particular interest (e.g., without human intervention, in certainembodiments). The anti-collision and motion control system describedherein is also capable of detecting operational activities taking placebased on multi-object tracking using a mesh network to interface betweenmultiple anti-collision and motion monitoring devices, and accuratelydelivering movement information, which will enhance the transparency ofthe operation and its current activity.

As such, the anti-collision and motion control system described hereinprovides a safe and intelligent tracking solution to manage assets inreal-time and provide telemetry readings to trend datasets, therebymaking facilities safer and environments more manageable. In particular,the anti-collision and motion control system described herein includes acombination of LiDAR technology, advanced high-fidelity visionprocessing, and integrated high-powered edge computing to accuratelyidentify and predict movements of people and machinery withincustomizable dedicated zones. Utilizing point cloud light data to detectobjects (e.g., machinery and people) combined with machine learningalgorithms to classify humans vs machines, for example, the embodimentsdescribed herein keep personnel and machinery safe while also increasingoperational efficiencies.

In addition, the embodiments described herein facilitate the addition ofa multitude of anti-collision and motion monitoring devices in a meshnetwork, wirelessly, in a plug-and-play manner, but also minimize thedata transferred between the anti-collision and motion monitoringdevices. In other words, instead of having all of the anti-collision andmotion monitoring devices transmitting data between all of the otheranti-collision and motion monitoring devices in the mesh network, theembodiments described herein intelligently determine what data needs tobe transmitted to which other anti-collision and motion monitoringdevices in the mesh network for the purpose of enabling theanti-collision and motion control system described herein to providemore robust control of the operations taking place within the physicalenvironment. In addition, because the data processing and transmissionrequirements of the anti-collision and motion monitoring devicesdescribed herein are minimized, the only cables that are required aredata cables and, indeed, in certain scenarios, even the data cables maybe omitted, with batteries being used in the anti-collision and motionmonitoring devices instead.

FIG. 1 is a schematic diagram of an anti-collision and motion controlsystem 10 using light detection and ranging (LiDAR) and high-fidelitycamera techniques, in accordance with embodiments the presentdisclosure. In particular, as illustrated in FIG. 1 , in certainembodiments, the anti-collision and motion control system 10 may includeone or more anti-collision and motion monitoring devices 12 and acentral coordinator 14 configured to coordinate operation of the one ormore anti-collision and motion monitoring devices 12 and one or moreindustrial control systems 16 that are used to control operatingparameters of machinery 18 disposed in a physical environment beingmonitored by the one or more anti-collision and motion monitoringdevices 12 (e.g., without human intervention, in certain embodiments).In addition, in certain embodiments, the central coordinator 14 may beconfigured to alert people 20 located in the physical environment beingmonitored by the one or more anti-collision and motion monitoringdevices 12, for example, when the people 20 move into areas of thephysical environment that the central coordinator 14 believes that thepeople 20 should not be.

As illustrated in FIG. 1 , each anti-collision and motion monitoringdevice 12 includes one or more light detection and ranging (LiDAR)modules 22, each configured to detect locations of one or more objects(e.g., machinery 18 and/or people 20) located in the physicalenvironment. As also illustrated in FIG. 1 , each anti-collision andmotion monitoring device 12 includes one or more camera modules 24configured to capture images of the one or more objects (e.g., machinery18 and/or people 20) located in the physical environment. In addition,as also illustrated in FIG. 1 , each anti-collision and motionmonitoring device 12 includes processing circuitry 26 configured tocoordinate operation of the one or more LiDAR modules 22 and the one ormore camera modules 24 by, for example, receiving inputs from the one ormore LiDAR modules 22 and the one or more camera modules 24 relating tothe one or more objects (e.g., machinery 18 and/or people 20) located inthe physical environment, processing the inputs received from the one ormore LiDAR modules 22 and the one or more camera modules 24 to determineoutputs relating to control of at least one of the one or more objects(e.g., machinery 18) located in the physical environment, and tocommunicate the outputs to a central coordinator 14, which includescontrol circuitry 28 configured to control one or more operatingparameters of at least one of the one or more objects (e.g., machinery18) located in the physical environment based at least in part on theinputs received from the one or more LiDAR modules 22 and the one ormore camera modules 24.

Although described primarily herein as utilizing anti-collision andmotion monitoring devices 12 that each include one or more LiDAR modules22 and one or more camera modules 24, in other embodiments, certainfeatures described herein may be accomplished with differentcombinations of types of cameras or light detection devices. Forexample, in certain embodiments, the anti-collision and motionmonitoring devices 12 may include only one or more LiDAR modules 22 oronly one or more camera modules 24 (e.g., either two-dimensional orthree-dimensional). In addition, in certain embodiments theanti-collision and motion monitoring devices 12 may include thermalcameras.

As will be appreciated, in certain embodiments, the processing circuitry26 of the anti-collision and motion monitoring devices 12 may include atleast one processor 30, at least one memory medium 32, at least onestorage medium 34, or any of a variety of other components that enablethe processing circuitry 26 to carry out the techniques describedherein. In addition, in certain embodiments, each anti-collision andmotion monitoring device 12 may include communication circuitry 36 tofacilitate the anti-collision and motion monitoring devices 12 tocommunicate with each other, as well as with the central coordinator 14,for example. In certain embodiments, the communication circuitry 36 maybe configured to facilitate wireless communication and/or wiredcommunication.

The at least one processor 30 of the anti-collision and motionmonitoring devices 12 may be any suitable type of computer processor ormicroprocessor capable of executing computer-executable code. In certainembodiments, the at least one processor 30 of the anti-collision andmotion monitoring devices 12 may also include multiple processors thatmay perform the operations described herein. The at least one memorymedium 32 and the at least one storage medium 34 of the anti-collisionand motion monitoring devices 12 may be any suitable articles ofmanufacture that can serve as media to store processor-executable code,data, or the like. These articles of manufacture may representcomputer-readable media (e.g., any suitable form of memory or storage)that may store the processor-executable code used by the at least oneprocessor 30 to perform the presently disclosed techniques. As describedin greater detail herein, the at least one memory medium 32 and the atleast one storage medium 34 of the anti-collision and motion monitoringdevices 12 may also be used to store data, various other softwareapplications, and the like. The at least one memory medium 32 and the atleast one storage medium 34 of the anti-collision and motion monitoringdevices 12 may represent non-transitory computer-readable media (e.g.,any suitable form of memory or storage) that may store theprocessor-executable code used by the at least one processor 30 toperform various techniques described herein. It should be noted thatnon-transitory merely indicates that the media is tangible and not asignal.

Similarly, in certain embodiments, the control circuitry 28 of thecentral coordinator 14 may include at least one processor 38, at leastone memory medium 40, at least one storage medium 42, or any of avariety of other components that enable the control circuitry 28 tocarry out the techniques described herein. In addition, in certainembodiments, the central coordinator 14 may include communicationcircuitry 44 to facilitate the central coordinator 14 to communicatewith the anti-collision and motion monitoring devices 12, for example.In certain embodiments, the communication circuitry 44 may be configuredto facilitate wireless communication and/or wired communication.

The at least one processor 38 of the central coordinator 14 may be anysuitable type of computer processor or microprocessor capable ofexecuting computer-executable code. In certain embodiments, the at leastone processor 38 of the central coordinator 14 may also include multipleprocessors that may perform the operations described herein. The atleast one memory medium 40 and the at least one storage medium 42 of thecentral coordinator 14 may be any suitable articles of manufacture thatcan serve as media to store processor-executable code, data, or thelike. These articles of manufacture may represent computer-readablemedia (e.g., any suitable form of memory or storage) that may store theprocessor-executable code used by the at least one processor 38 toperform the presently disclosed techniques. As described in greaterdetail herein, the at least one memory medium 40 and the at least onestorage medium 42 of the central coordinator 14 may also be used tostore data, various other software applications, and the like. The atleast one memory medium 40 and the at least one storage medium 42 of thecentral coordinator 14 may represent non-transitory computer-readablemedia (e.g., any suitable form of memory or storage) that may store theprocessor-executable code used by the at least one processor 38 toperform various techniques described herein. It should be noted thatnon-transitory merely indicates that the media is tangible and not asignal.

To better illustrate the functionality of the anti-collision and motioncontrol system 10 of FIG. 1 , FIG. 2 is a perspective view of a physicalenvironment 46 (e.g., a drill rig, a plant floor, and so forth) that maybe monitored by the anti-collision and motion control system 10, inaccordance with embodiments the present disclosure. As illustrated inFIG. 2 , one or more pieces of machinery 18 may be disposed in thephysical environment 46, and various people 20 may wander through thephysical environment 46, for example, to perform work duties, observeoperations within the physical environment 46, and so forth. Althoughillustrated in FIG. 2 as having four anti-collision and motionmonitoring devices 12 monitoring the physical environment 46, in otherembodiments, any number of anti-collision and motion monitoring devices12 may be used to monitor the physical environment 46.

The one or more LiDAR modules 22 of the anti-collision and motionmonitoring devices 12 are configured to detect locations of one or moreobjects (e.g., machinery 18 and/or people 20) located in the physicalenvironment 46. For example, the one or more LiDAR modules 22 of theanti-collision and motion monitoring devices 12 are configured to emitpulses of laser light into the physical environment 46, to detect pulsesthat are reflected off of the objects (e.g., machinery 18 and/or people20) located in the physical environment 46, and to determine locationsof the objects (e.g., machinery 18 and/or people 20) located in thephysical environment 46 based on the reflected pulses. Morespecifically, the one or more LiDAR modules 22 of the anti-collision andmotion monitoring devices 12 are configured to consider return time ofthe reflected pulses, differences in wavelengths of the reflectedpulses, and so forth, to determine a three-dimensional mapping of thephysical environment 46, which may be processed by the processingcircuitry 26 of the respective anti-collision and motion monitoringdevice 12 to detect locations of specific objects (e.g., machinery 18and/or people 20) located in the physical environment 46 and, indeed, toclassify the detected objects (e.g., machinery 18 and/or people 20)located in the physical environment 46 based at least in part on thedetection performed by the LiDAR modules 22. For example, the processingcircuitry 26 may identify the objects (e.g., machinery 18 and/or people20) located in the physical environment 46 as particular types ofmachinery 18, specific people 20, and so forth, based at least in parton the detection performed by the LiDAR modules 22.

In addition, the one or more camera modules 24 of the anti-collision andmotion monitoring devices 12 are configured to capture images of the oneor more objects (e.g., machinery 18 and/or people 20) located in thephysical environment 46, which may also be processed by the processingcircuitry 26 of the respective anti-collision and motion monitoringdevice 12 to classify the detected objects (e.g., machinery 18 and/orpeople 20) located in the physical environment 46 based at least in parton the images captured by the camera modules 24. For example, theprocessing circuitry 26 may identify the objects (e.g., machinery 18and/or people 20) located in the physical environment 46 as particulartypes of machinery 18, specific people 20, and so forth, based at leastin part on the images captured by the camera modules 24.

FIG. 3 are perspective views of a plurality of anti-collision and motionmonitoring devices 12 of the anti-collision and motion control system 10of FIG. 1 , in accordance with embodiments the present disclosure. Asillustrated in FIG. 3 , in certain embodiments, the one or more LiDARmodules 22, the one or more camera modules 24, and the processingcircuitry 26 of each anti-collision and motion monitoring device 12 maybe integrated together within a common housing of the anti-collision andmotion monitoring device 12. As such, the anti-collision and motionmonitoring devices 12 described herein are fully self-contained packagescapable of being deployed in various types of physical environments 46,and coordinated via a central coordinator 14, as illustrated in FIG. 1 .In addition, as illustrated in FIG. 3 , in certain embodiments, theanti-collision and motion monitoring devices 12 may include a pluralityof antennae 48, which may be part of the communication circuitry 36 ofthe anti-collision and motion monitoring devices 12, as well as servinga secondary function as legs for the anti-collision and motionmonitoring devices 12.

Returning now to FIG. 1 , the central coordinator 14 of theanti-collision and motion control system 10 may establish acommunication network 50 between the various anti-collision and motionmonitoring devices 12 monitoring a particular physical environment 46.In other words, the communication circuitry 44 of the centralcoordinator 14 and the communication circuitry 36 of the variousanti-collision and motion monitoring devices 12 monitoring a particularphysical environment 46 may each communicate with each other in anon-hierarchical manner (e.g., as a mesh network) in real-time such thateach of the components has access to the same data as the others. Incertain embodiments, the communication network 50 may be a wirelesscommunication network (e.g., using Wi-Fi, Bluetooth, or other wirelesscommunication techniques) to facilitate rapid and more flexibledeployment of the anti-collision and motion monitoring devices 12 inparticular physical environments 46.

In certain embodiments, the communication network 50 may include varioussubnetworks including, but not limited to, a local mesh network and ademilitarized zone (DMZ) network, both of which may communicate witheach other via other communication techniques including, but not limitedto, one or more firewalls, the Internet, satellite networks, and soforth. In general, the local mesh network may include one or moreanti-collision and motion monitoring devices 12, which are deployed inone or more physical environments 46 being monitored by the centralcoordinator 14, which may be part of the DMZ network, which also mayinclude one or more storage media, such as a central archive storageserver. In addition, in certain embodiments, software applicationsrunning on computing devices in the DMZ network may, for example,provide visualization functionality related to the monitoring andcontrol provided by the anti-collision and motion control system 10.

In certain embodiments, the central coordinator 14 may include devicesand/or software that provide an edge gateway for the one or moreanti-collision and motion monitoring devices 12, such that theprocessing circuitry 26 of the one or more anti-collision and motionmonitoring devices 12 may preprocess the data that is collected (e.g.,by the respective one or more LiDAR modules 22 and the respective one ormore camera modules 24) before providing it to the central coordinator14. For example, once the processing circuitry 26 of the one or moreanti-collision and motion monitoring devices 12 preprocess the datacollected by the respective one or more LiDAR modules 22 and therespective one or more camera modules 24, the one or more anti-collisionand motion monitoring devices 12 may communicate with the centralcoordinator 14 via the mesh network, which may in certain embodimentsinclude one or more wireless application protocol (WAP) devices, one ormore sensor relays, one or more layer switches, and so forth, which mayfacilitate communication between the one or more anti-collision andmotion monitoring devices 12 and the central coordinator 14 via the meshnetwork.

It should be noted that, in certain embodiments, the LiDAR modules 22,the camera modules 24, the processing circuitry 26, and/or thecommunication circuitry 36 of the anti-collision and motion monitoringdevices 12 may actually include multiple instances of each, such thatthe LiDAR modules 22, the camera modules 24, the processing circuitry26, and/or the communication circuitry 36 are redundant for theanti-collision and motion monitoring devices 12, thereby enhancing therobustness of the anti-collision and motion monitoring devices 12. Forexample, in certain embodiments, the anti-collision and motionmonitoring devices 12 may include two, three, or even more, of the LiDARmodules 22 and of the camera modules 24. In addition, in certainembodiments, the anti-collision and motion monitoring devices 12 mayinclude two or more instances of the processing circuitry 26, Inaddition, in certain embodiments, the anti-collision and motionmonitoring devices 12 may include two or more instances of thecommunication circuitry 36 as redundant for the purposes ofcommunicating the telemetry data of the objects (e.g., machinery 18and/or people 20) located in the physical environment 46 via a meshnetwork, as described herein, as well as two or more instances of thecommunication circuitry 36 as redundant for the purposes ofcommunicating archive data, backup data, updates, and so forth, betweenthe anti-collision and motion monitoring devices 12 in the mesh network.

FIG. 4 is a schematic diagram of the processing circuitry 26 of theanti-collision and motion monitoring devices 12, in accordance withembodiments the present disclosure. In particular, FIG. 4 illustratesvarious modules (e.g., hardware modules, software modules,hardware/software modules, and so forth) that are configured, forexample, to coordinate operation of the LiDAR modules 22 and the cameramodules 24 of the respective anti-collision and motion monitoring device12, to receive inputs from the LiDAR modules 22 and the camera modules24 of the respective anti-collision and motion monitoring device 12relating to objects (e.g., machinery 18 and/or people 20) located in thephysical environment 46, to process the inputs received from the LiDARmodules 22 and the camera modules 24 of the respective anti-collisionand motion monitoring device 12 to determine outputs relating to controlof at least one of the objects (e.g., machinery 18 and/or people 20)located in the physical environment 46, to communicate the outputs tothe central coordinator 14 to control one or more operating parametersof at least one of the objects (e.g., machinery 18) located in thephysical environment 46 based at least in part on the inputs receivedfrom the LiDAR modules 22 and the camera modules 24 of the respectiveanti-collision and motion monitoring device 12, and so forth.

As illustrated in FIG. 4 , in certain embodiments, the processingcircuitry 26 may include a static zoning module 52 configured to receiveinputs 54 from the LiDAR modules 22 of the respective anti-collision andmotion monitoring device 12, and to perform static zoning of locationsof objects (e.g., machinery 18 and/or people 20) located in the physicalenvironment 46, which are detected by the LiDAR modules 22. For example,in certain embodiments, the static zoning module 52 may include one ormore sub-modules that are configured to perform motion filtering 52A,light filtering 52B, point cloud filtering 52C, and various combinationsthereof. In addition, in certain embodiments, the processing circuitry26 may also include a dynamic zoning module 56 configured to performdynamic zoning of the locations of the objects (e.g., machinery 18and/or people 20) located in the physical environment 46, which aredetected by the LiDAR modules 22, based on the static zoning performedby the static zoning module 52. In general, the static zoning module 52and the dynamic zoning module 56 of the processing circuitry 26 areconfigured to function together to monitor the physical environment 46for the purpose of aiding in the tracking of the objects (e.g.,machinery 18 and/or people 20) located in the physical environment 46.In certain embodiments, the static zoning module 52 may capturesnapshots of the physical environment 46 periodically, and may use apoint of reference to calibrate the real-time filtering of staticobjects within the physical environment 46. For example, some identifiedobjects in the physical environment 46 (e.g., windows, wall structuressuch as beams, and so forth) may be known to never move, and theseobjects may be used to calibrate the real-time filtering of staticobjects within the physical environment 46. As such, the amount ofcomputing and the speed of computing may be reduced.

As illustrated in FIG. 4 , in certain embodiments, the processingcircuitry 26 may also include an active zone detection module 58configured to determine which zones of a plurality of zones of thephysical environment are active (e.g., which currently have, or recentlyhave, had movement of objects occur within them), and the dynamic zoningmodule 56 may perform the dynamic zoning of the locations of the objects(e.g., machinery 18 and/or people 20) located in the physicalenvironment 46 based at least in part on the active zones in thephysical environment 46, which are determined by the active zonedetection module 58. For example, in certain embodiments, the activezone detection module 58 may determine the active zones in the physicalenvironment 46 based on the object tracking performed by the processingcircuitry 26, as described herein, and/or based on communications withthe central coordinator 14. In other words, in certain embodiments, theactive zones in the physical environment 46 may be based on detection ofrecent motion within the physical environment 46, may be predeterminedby the central coordinator 14, may be predetermined by the centralcoordinator 14 but modified upon detection of recent motion within thephysical environment 46, and so forth. The ability to only performdynamic zoning of active zones, as determined by the active zonedetection module 58, may reduce the processing cycles required by thedynamic zoning module 56, as well as reduce the amount of data that willbe communicated to the central coordinator 14.

In addition, in certain embodiments, the processing circuitry 26 mayinclude an image acquisition module 60 configured to acquire images 62of the objects (e.g., machinery 18 and/or people 20) located in thephysical environment 46, which are captured by the camera modules 24 ofthe respective anti-collision and motion monitoring device 12. Inaddition, in certain embodiments, the processing circuitry 26 may alsoinclude an object property identification module 64 configured toidentify properties (e.g., identification of object types, such as typesof machinery, whether the object is a person, whether the object isstationary or in motion, and so forth) of at least one of the objects(e.g., machinery 18 and/or people 20) located in the physicalenvironment 46 based at least in part on the images 62 acquired by theimage acquisition module 60. In addition, in certain embodiments, theprocessing circuitry 26 may also include an object classification module66 configured to classify at least one of the objects (e.g., machinery18 and/or people 20) located in the physical environment 46 based atleast in part on the images 62 acquired by image acquisition module 60.In addition, in certain embodiments, the processing circuitry 26 mayalso include an object tracking module 68 configured to track location,orientation, or motion of at least one of the objects (e.g., machinery18 and/or people 20) located in the physical environment 46 based atleast in part on the images 62 acquired by image acquisition module 60.In addition, in certain embodiments, the object tracking module 68 maybe configured to track location, orientation, or motion of at least oneof the objects (e.g., machinery 18 and/or people 20) located in thephysical environment 46 based at least in part on input from the dynamiczoning module 56 of the processing circuitry 26.

In addition, in certain embodiments, the processing circuitry 26 mayinclude a communication module 70 configured to communicate (e.g.,wirelessly via the communication circuitry 36, in certain embodiments;however, wired communication may also be used) outputs 72 from theprocessing circuitry 26 to the central coordinator 14 and, in certainembodiments, to processing circuitry 26 of other anti-collision andmotion monitoring devices 12. For example, in certain embodiments, theoutputs 72 may be communicated between the various anti-collision andmotion monitoring devices 12 (e.g., via a mesh network) to reducenetwork latency, for example. In such embodiments, one of theanti-collision and motion monitoring devices 12 may function as a masterfor all of the other anti-collision and motion monitoring devices 12such that the master anti-collision and motion monitoring device 12coordinates the communication of outputs 72 from the various otheranti-collision and motion monitoring devices 12 to the centralcoordinator 14. Furthermore, in certain embodiments, the anti-collisionand motion monitoring devices 12 may only make requests of data fromother anti-collision and motion monitoring devices 12 when thatparticular data is needed for the processing of the particularanti-collision and motion monitoring device 12, in order to minimize theamount of data being transferred via the mesh network. For example, incertain embodiments, if one anti-collision and motion monitoring device12 is tracking a particular object, but loses a line of sight (e.g., anunobstructed view of the particular object by the LiDAR modules 22 orthe camera modules 24 of the anti-collision and motion monitoring device12 is at least partially lost) of the object, that particularanti-collision and motion monitoring device 12 may send a request toanother anti-collision and motion monitoring device 12 to provide datarelating to the object for which the line of sight has been lost. Assuch, the anti-collision and motion monitoring devices 12 may functiontogether in a coordinated manner of “swarm processing” whereby data fromthe various anti-collision and motion monitoring devices 12 may bestitched together to give the central coordinator 14 a collective viewof objects (e.g., machinery 18 and/or people 20) monitored by thevarious anti-collision and motion monitoring devices 12.

In certain embodiments, at least some of the outputs 72 communicated tothe central coordinator 14 from an anti-collision and motion monitoringdevice 12 may relate to the location, orientation, or motion of at leastone of the objects (e.g., machinery 18 and/or people 20) located in thephysical environment 46 (i.e., telemetry data of the objects), which istracked by the object tracking module 68 of the anti-collision andmotion monitoring device 12. Furthermore, in certain embodiments, thecommunication module 70 may be configured to receive information fromthe central coordinator 14, such as which zones of the physicalenvironment 46 are active (e.g., for input into the active zonedetection module 58 of the processing circuitry 26). In addition, incertain embodiments, the processing circuitry 26 may include an archivestorage module 74 configured to store data from any of the variousmodules of the processing circuitry 26 (e.g., data relating to theinputs 54 from the LiDAR modules 22, data relating to the images 62captured by the camera modules 24 and acquired by the image acquisitionmodule 60, data relating to outputs 72 communicated to the centralcoordinator 14, or any other data processed by the various modules ofthe processing circuitry 26).

In general, the various modules of the processing circuitry 26 of theanti-collision and motion monitoring devices 12 may be considered asdistinct processing groups of modules that cooperate with each other forthe purpose of tracking objects (e.g., machinery 18 and/or people 20)located in the physical environment 46. For example, the static zoningmodule 52 may be considered as part of a LiDAR processing group 76 ofmodules, the image acquisition module 60, the object propertyidentification module 64, and the object classification module 66 may beconsidered as part of an image processing group 78 of modules, and thedynamic zoning module 56, the active zone detection module 58, theobject tracking module 68, and the communication module 70 may beconsidered as part of a core processing group 80 of modules.

In addition, in certain embodiments, the processing circuitry 26 of theanti-collision and motion monitoring devices 12 may include other, ordifferent, modules not shown in FIG. 4 . For example, in certainembodiments, the LiDAR processing group 76 of modules may include anobject property identification module 64 and an object classificationmodule 66 (e.g., between the static zoning module 52 and the dynamiczoning module 56) instead of, or in addition to, the object propertyidentification module 64 and the object classification module 66 of theimage processing group 78 of modules, which may perform object propertyidentification and object classification, respectively, based on theinputs 54 from the LiDAR modules 22, instead of based on the images 62acquired by the image acquisition module 60. In such embodiments, theobject property identification module 64 and the object classificationmodule 66 of the LiDAR processing group 76 of modules may be used tocheck the results of the object property identification module 64 andthe object classification module 66 of the image processing group 78 ofmodules and/or to calibrate the processing of the object propertyidentification module 64 and the object classification module 66 of theimage processing group 78 of modules.

In addition, in certain embodiments, in the interest of reducing theprocessing required of the various modules of the processing circuitry26 of the anti-collision and motion monitoring devices 12, as well asreduce the amount of data being transferred via the mesh network, incertain embodiments, certain of the modules of the processing circuitry26 may not continually perform their processing, but may rather onlyperform their particular processing tasks when requested by one of theother modules of the processing circuitry 26. As but one non-limitingexample, in certain embodiments, once an object has been classified bythe object classification module 66, the object classification module 66may not be requested to classify any other objects until additionalmotion (e.g., not relating to any presently classified objects) isdetected by the static and dynamic zoning modules 52, 56 and/or when theobject tracking module 68 requests that an object be re-identified(e.g., in a situation where the object disappears from a line of sightof the particular anti-collision and motion monitoring device 12temporarily).

FIG. 5 is a schematic diagram of the control circuitry 28 of the centralcoordinator 14, in accordance with embodiments the present disclosure.In particular, FIG. 5 illustrates various modules (e.g., hardwaremodules, software modules, hardware/software modules, and so forth) thatare configured, for example, to receive the outputs 72 from theprocessing circuitry 26 of the one or more anti-collision and motionmonitoring devices 12, and to control one or more operating parametersof at least one of the objects (e.g., machinery 18) located in thephysical environment 46 based at least in part on the outputs 72received from the processing circuitry 26 of the one or moreanti-collision and motion monitoring devices 12.

For example, as illustrated in FIG. 5 , in certain embodiments, thecontrol circuitry 28 may include a communication module 82 configured toreceive (e.g., wirelessly via the communication circuitry 44, in certainembodiments; however, wired communication may also be used) the outputs72 from the processing circuitry 26 of the one or more anti-collisionand motion monitoring devices 12. Indeed, the communication module 82 ofthe control circuitry 28 may be configured to bi-directionallycommunicate with the communication modules 70 of the one or moreanti-collision and motion monitoring devices 12 to transfer data betweenthe central coordinator 14 and the one or more anti-collision and motionmonitoring devices 12, as described in greater detail herein.

In addition, in certain embodiments, the control circuitry 28 mayinclude one or more industrial control module(s) 84 configured tocommunicate control signals 86 (e.g., stop commands, and so forth) toone or more industrial control systems 16 to control one or moreoperating parameters of at least one of the objects (e.g., machinery 18)located in the physical environment 46 based at least in part on theoutputs 72 received from the one or more anti-collision and motionmonitoring devices 12 and/or based at least in part on information fromone or more physics models, as described in greater detail herein. Inaddition, in certain embodiments, the industrial control module(s) 84may be configured to perform control system validation. For example, incertain embodiments, the industrial control module(s) 84 may receivefeedback signals from the industrial control systems 16 during operationof the industrial control systems 16, which may be used to validate thecontrol signals 86 that are being communicated to the industrial controlsystems 16 are effecting the one or more operating parameters of theobjects (e.g., machinery 18) located in the physical environment 46 thatare being controlled. In addition, in certain embodiments, positioningencoders in the industrial control systems 16 may provide informationrelating to locations of the industrial control systems 16 within thephysical environment 46, and the industrial control module(s) 84 may beconfigured to validate this location information based on objecttracking performed by the control circuitry 28.

In addition, in certain embodiments, the control circuitry 28 may alsoinclude an archive storage module 88 configured to store data from anyof the various modules of the control circuitry 28 (e.g., data relatingto the outputs 72 received from the one or more anti-collision andmotion monitoring devices 12, data relating to the control signals 86communicated to the ICSs, or any other data processed by the variousmodules of the control circuitry 28). For example, in certainembodiments, as the outputs 72 from the one or more anti-collision andmotion monitoring devices 12 (e.g., the telemetry data relating to oneor more tracked objects) are received by the communication module 82,raw data relating to the outputs 72 may be stored in the archive storagemodule 88, and the raw data may be processed by the control circuitry28, as described in greater detail herein, and the processed data may bestored in a separate database 90. In certain embodiments, the raw datamay also be synched to cloud storage, for example. In addition, incertain embodiments, the control circuitry 28 may be configured tocommunicate software updates 92 to the processing circuitry 26 of theone or more anti-collision and motion monitoring devices 12.

In addition, in certain embodiments, the control circuitry 28 may beconfigured to control one or more operating parameters of at least oneof the objects (e.g., machinery 18) located in the physical environment46 based at least in part on one or more physics models 94, for example,stored in memory of the control circuitry 28. For example, in certainembodiments, the control circuitry 28 may be configured to control oneor more operating parameters of at least one of the objects (e.g.,machinery 18) located in the physical environment 46 based at least inpart on one or more acceleration vectors 94A relating to at least one ofthe objects (e.g., machinery 18 and/or people 20) located in thephysical environment 46. In addition, in certain embodiments, thecontrol circuitry 28 may be configured to control one or more operatingparameters of at least one of the objects (e.g., machinery 18) locatedin the physical environment 46 based at least in part on one or morecollision vectors 94B relating to at least one of the objects (e.g.,machinery 18 and/or people 20) located in the physical environment 46.In addition, in certain embodiments, the control circuitry 28 may beconfigured to control one or more operating parameters of at least oneof the objects (e.g., machinery 18) located in the physical environment46 based at least in part on one or more exact coordinates 94C of atleast one of the objects (e.g., machinery 18 and/or people 20) locatedin the physical environment 46. In addition, in certain embodiments, thecontrol circuitry 28 may be configured to control one or more operatingparameters of at least one of the objects (e.g., machinery 18) locatedin the physical environment 46 based at least in part on one or moreconflict resolutions 94D relating to at least one of the objects (e.g.,machinery 18 and/or people 20) located in the physical environment 46.

In certain embodiments, the one or more physics models 94 may enable thecontrol circuitry 28 to predict a future location, orientation, ormotion of at least one of the objects (e.g., machinery 18 and/or people20) located in the physical environment 46 based at least in part onprevious location, orientation, or motion of the at least one of theobjects (e.g., machinery 18 and/or people 20) located in the physicalenvironment 46. For example, in certain embodiments, the one or morephysics models 94 may include data relating to movement trajectoriesthat are commonly tracked for a particular object (e.g., machinery 18and/or people 20) that has been identified by the object propertyidentification module 64 of the processing circuitry 26 of the one ormore anti-collision and motion monitoring devices 12, for example, andthe control circuitry 28 may use the data relating to the movementtrajectories to predict a future location, orientation, or motion of theparticular object. For example, a certain identified person 20 may havecommon movement patterns while in the physical environment 46 (e.g.,while inspecting the machinery 18). Similarly, a certain piece ofmachinery 18 may have common movement patterns during operation. Thesetypes of common movement patterns may be used by the control circuitry28 to predict future location, orientation, or motion of the particularobject, which may be used to control one or more operating parameters ofat least one of the objects (e.g., machinery 18) located in the physicalenvironment 46, as described in greater detail herein.

In addition, in certain embodiments, the control circuitry 28 mayinclude a visualization/UI engine 96 configured to provide one or morevisualizations of the physical environment 46 to a user interface 98communicatively coupled to the central coordinator 14. In particular,the visualization/UI engine 96 may provide an application programinterface (API) that the user interface 98 may access in order toprovide the one or more visualizations of the physical environment 46based at least in part on the processed data stored in the database 90,for example.

Similar to the processing circuitry 26 of the anti-collision and motionmonitoring devices 12, the various modules of the control circuitry 28of the central coordinator 14 may be considered as distinct processinggroups of modules that cooperate with each other for the purpose ofcontrolling objects (e.g., machinery) located in the physicalenvironment 46. For example, the communication module 82, the archivestorage module 88, and the industrial control module(s) 84 may beconsidered as part of a data processing control group 100 of modules,and the database 90, the physics models 94, and the visualization/UIengine 96 may be considered as part of a UI group 102 of modules.

As described in greater detail herein, the anti-collision and motionmonitoring devices 12 may be specifically configured to cooperate witheach other to automatically form a mesh network of connectivity when theanti-collision and motion monitoring devices 12 are operating in closeproximity with each other. For example, in certain embodiments, whenmore than one anti-collision and motion monitoring devices 12 aredeployed within a particular physical environment 46 and within aparticular range (e.g., within 100 feet, within 200 feet, within 300feet, within 500 feet, and so forth), the anti-collision and motionmonitoring devices 12 may automatically establish communications witheach other (e.g., via the communication circuitry 36 of theanti-collision and motion monitoring devices 12) to communicativelycouple the anti-collision and motion monitoring devices 12 together witheach other in a mesh network, such that the anti-collision and motionmonitoring devices 12 may coordinate with each other to monitormachinery 18 and/or people 20 within the physical environment 46. Inparticular, if neither of the anti-collision and motion monitoringdevices 12 communicating with each other had previously beencommunicatively coupled into a mesh network (e.g., with otheranti-collision and motion monitoring devices 12), a new mesh network maybe created by the anti-collision and motion monitoring devices 12.However, if one of the anti-collision and motion monitoring devices 12communicating with each other had previously been communicativelycoupled into a mesh network, the other anti-collision and motionmonitoring device 12 may then join the previously-established meshnetwork. In certain embodiments, the anti-collision and motionmonitoring devices 12 joining the mesh network may be required toprovide authenticating information (e.g., which may be stored in the atleast one memory medium 32 and/or the at least one storage medium 34 ofthe respective anti-collision and motion monitoring device 12) to theother anti-collision and motion monitoring device 12.

FIG. 6 is a simplified example of a rectilinear grid 104 representing aphysical environment 46 that may be monitored by one or moreanti-collision and motion monitoring devices 12. In particular, asillustrated in FIG. 6 , the physical environment 46 is being monitoredby a first anti-collision and motion monitoring device 12A, a secondanti-collision and motion monitoring device 12B, and a thirdanti-collision and motion monitoring device 12C. Although illustrated inFIG. 6 as being a two-dimensional rectilinear grid 104 for ease ofexplanation, it will be appreciated that the rectilinear grid 104 mayindeed include a third dimension, and that the techniques describedherein may be extended to the third dimension. As described herein, whenthe anti-collision and motion monitoring devices 12A, 12B, 12C arecommunicatively coupled into a mesh network with each other, theanti-collision and motion monitoring devices 12A, 12B, 12C maycoordinate with each other to ensure that as much of the physicalenvironment 46 is continually monitored as possible. In particular, theanti-collision and motion monitoring devices 12A, 12B, 12C maycommunicate with each other to complement the data that is detected bythe respective anti-collision and motion monitoring device 12A, 12B,12C.

For example, as described in greater detail herein, each of theanti-collision and motion monitoring devices 12A, 12B, 12C may beconfigured to individually monitor the physical environment 46 byitself, for example, by detecting data relating to presence and/ormovement of machinery 18 and/or people 20 in the physical environment 46and requesting complementary data from another anti-collision and motionmonitoring device 12A, 12B, 12C only when such data would likely enhancethe monitoring being performed by the respective anti-collision andmotion monitoring device 12A, 12B, 12C. In particular, in certainembodiments, an anti-collision and motion monitoring device 12A, 12B,12C may request complementary data from another anti-collision andmotion monitoring device 12A, 12B, 12C only when there is a particularsection 106 of the rectilinear grid 104 to which the respectiveanti-collision and motion monitoring device 12A, 12B, 12C does not haveline of sight. In addition, in certain embodiments, an anti-collisionand motion monitoring device 12A, 12B, 12C may request complementarydata from another anti-collision and motion monitoring device 12A, 12B,12C only when such data would likely enhance the monitoring beingperformed by the respective anti-collision and motion monitoring device12A, 12B, 12C. For example, in certain embodiments, an anti-collisionand motion monitoring device 12A, 12B, 12C may request complementarydata from another anti-collision and motion monitoring device 12A, 12B,12C only when the respective anti-collision and motion monitoring device12A, 12B, 12C is currently tracking a piece of machinery 18 and/or aperson 20 having a currently tracked position in and/or a currentmovement trajectory into a particular section 106 of the rectilineargrid 104 (e.g., in a zone of particular interest, such as a “hot zone”,as described in greater detail herein), and another anti-collision andmotion monitoring device 12A, 12B, 12C is determined to have data thatwould complement the data locally detected by the respectiveanti-collision and motion monitoring device 12A, 12B, 12C (e.g., whichmay be referred to as “primary” data). In other words, in certainembodiments, an anti-collision and motion monitoring device 12A, 12B,12C may individually monitor a physical environment 46 by itself, andonly request complementary data from another anti-collision and motionmonitoring device 12A, 12B, 12C at times when the respectiveanti-collision and motion monitoring device 12A, 12B, 12C does not haveline of sight to a particular section 106 of the rectilinear grid 104and when the respective anti-collision and motion monitoring device 12A,12B, 12C would benefit from complementary data from anotheranti-collision and motion monitoring device 12A, 12B, 12C. As such, thedata transferred between the anti-collision and motion monitoringdevices 12A, 12B, 12C via the mesh network may be minimized insofar asdata is only transferred between anti-collision and motion monitoringdevices 12A, 12B, 12C when the data is required by a particularanti-collision and motion monitoring device 12A, 12B, 12C.

In certain embodiments, each of the anti-collision and motion monitoringdevices 12A, 12B, 12C may store (e.g., in the at least one memory medium32 and/or the at least one storage medium 34 of the respectiveanti-collision and motion monitoring device 12) data relating topositioning and orientation of the other anti-collision and motionmonitoring devices 12A, 12B, 12C for the purpose of determining whenanother anti-collision and motion monitoring device 12A, 12B, 12C may bepositioned and oriented in a manner that would enable one of the otheranti-collision and motion monitoring device 12A, 12B, 12C to providecomplementary data to the respective anti-collision and motionmonitoring device 12A, 12B, 12C, for example, when the respectiveanti-collision and motion monitoring device 12A, 12B, 12C does not haveline of sight to a particular section 106 of the rectilinear grid 104and when the respective anti-collision and motion monitoring device 12A,12B, 12C would benefit from complementary data from the otheranti-collision and motion monitoring device 12A, 12B, 12C. In certainembodiments, the data relating to positioning and orientation of theother anti-collision and motion monitoring devices 12A, 12B, 12C may becommunicated between the anti-collision and motion monitoring devices12A, 12B, 12C at the time that the anti-collision and motion monitoringdevices 12A, 12B, 12C are communicatively coupled to each other. Inaddition, in certain embodiments, the data relating to positioning andorientation of the other anti-collision and motion monitoring devices12A, 12B, 12C may be communicated between the anti-collision and motionmonitoring devices 12A, 12B, 12C through periodic updates that occur atparticular time intervals (e.g., every hour, every 30 minutes, every 15minutes, every 10 minutes, every 5 minutes, every minute, or even morefrequently).

To illustrate how the anti-collision and motion monitoring devices 12A,12B, 12C may cooperate with each other to monitor a physical environment46, FIG. 6 depicts an example physical environment 46 that includes fivegrid sections 108A, 108B, 108C, 108D, 108E that currently include atleast a portion of machinery 18 (M) and two grid sections 110A, 110Bthat currently include at least a portion of a person 20 (P). In theexample layout illustrated in FIG. 6 , an anti-collision and motionmonitoring device 12C may not have line of sight of a grid section 110Bthat includes at least a portion of a person 20 (P). As such, at thispoint in time, the anti-collision and motion monitoring device 12C mayrequest complementary data from either of the other anti-collision andmotion monitoring devices 12A, 12B. However, again, in certainembodiments, to minimize data transfer via the mesh network establishedbetween the anti-collision and motion monitoring devices 12A, 12B, 12C,the anti-collision and motion monitoring device 12C may only requestcomplementary data from one, but not both, of the other anti-collisionand motion monitoring devices 12A, 12B.

Many parameters may be considered by the anti-collision and motionmonitoring device 12C when determining which of the other anti-collisionand motion monitoring devices 12A, 12B would be the best option fromwhich to request data. One parameter that may be used by theanti-collision and motion monitoring device 12C may be proximity betweenthe anti-collision and motion monitoring device 12C and the otheranti-collision and motion monitoring devices 12A, 12B. For example, ifthe anti-collision and motion monitoring device 12C is closer to theanti-collision and motion monitoring device 12A than to theanti-collision and motion monitoring device 12B, then the anti-collisionand motion monitoring device 12C may request complementary data from theanti-collision and motion monitoring device 12A. Another parameter thatmay be used by the anti-collision and motion monitoring device 12C maybe a confidence level that each of the other anti-collision and motionmonitoring devices 12A, 12B is capable of providing the complementarydata for the grid section 110B of interest to the anti-collision andmotion monitoring device 12C such that the data will prove useful to theanti-collision and motion monitoring device 12C. For example, if theanti-collision and motion monitoring device 12B has a clear line ofsight of the grid section 110B of interest to the anti-collision andmotion monitoring device 12C than the anti-collision and motionmonitoring device 12A, then the confidence level of the anti-collisionand motion monitoring device 12B may be higher than that of theanti-collision and motion monitoring device 12A. Yet another parameterthat may be used by the anti-collision and motion monitoring device 12Cmay be signal strength from the other anti-collision and motionmonitoring devices 12A, 12B, which may be detected by the anti-collisionand motion monitoring device 12C. For example, if the anti-collision andmotion monitoring device 12C detects a greater signal strength from theanti-collision and motion monitoring device 12A than from theanti-collision and motion monitoring device 12B, then the anti-collisionand motion monitoring device 12C may request complementary data from theanti-collision and motion monitoring device 12A. It will be appreciatedthat any combination of these parameters, as well as other parametersrelating to the probability that one of the other anti-collision andmotion monitoring devices 12A, 12B may be capable of providingsufficient complementary data, may be used by the anti-collision andmotion monitoring device 12C. In certain embodiments, data relating tothese parameters may be requested from the other anti-collision andmotion monitoring devices 12A, 12B by the anti-collision and motionmonitoring device 12C as a ping request to receive the data relating tothese parameters before initiating a data stream relating to the gridsection 110B of interest from a selected other anti-collision and motionmonitoring device 12A, 12B.

As described in greater detail herein, the software algorithms employedby the processing circuitry 26 of the anti-collision and motionmonitoring devices 12 and the control circuitry 28 of the centralcoordinator 14 consist of a multi-staged approach to solving the issueof finding, tracking, and identifying objects (e.g., machinery 18 and/orpeople 20) within a defined area (e.g., a defined physical environment46). As described in greater detail herein, this multi-staged approachconsists of an embedded backend device layer (e.g., in theanti-collision and motion monitoring devices 12, in certainembodiments), a high-level middleware layer (e.g., in the centralcoordinator 14, in certain embodiments), and a configurable UI frontend(e.g., in the central coordinator 14, in certain embodiments). As alsodescribed in greater detail herein, the backend device layer combinesfull data capture and masking of static objects, followed by filteringof, for example, a boxed area of the physical environment 46 andcompensation for angles of deflection, for example. In certainembodiments, the backend device layer clusters the remaining dataregions, and computes a linear interpolation of a flat x/y grid model(e.g., similar to the rectilinear grid 104 illustrated in FIG. 6 )within a fixed area of the physical environment 46. In general, thebackend device layer identifies the location and type of objects (e.g.,machinery 18 and/or people 20) using machine learning, and moves thedata to the middleware layer for further analysis.

In certain embodiments, the software algorithms employed by theprocessing circuitry 26 of the anti-collision and motion monitoringdevices 12 and the control circuitry 28 of the central coordinator 14acquire a three-dimensional space, and create a two-dimensional flatgrid (e.g., similar to the rectilinear grid 104 illustrated in FIG. 6 )within the layered three-dimensional region. In certain embodiments, thegrid defining the physical environment 46 may be allocated anddistributed based on data read in from a configuration file. In certainembodiments, the anti-collision and motion monitoring devices 12translate data from a point cloud space to grid coordinates, asdescribed in greater detail herein. In certain embodiments, a pluralityof grids relating to the physical environment 46 may be created, whichmay slightly overlap such that if one anti-collision and motionmonitoring device 12 fails to capture certain point cloud data, anotheranti-collision and motion monitoring device 12 may capture the pointcloud data, and send it to the middleware layer for processing.

In certain embodiments, to take into account the zero indexing ofstoring the data, the embedded device layer may apply an offset to bringall negative values in the x-axis to zero, for example, so that theentire grid is shifted, which may be applied by the middleware layer. Incertain embodiments, the middleware layer may or may not apply thisoffset, but rather may assume that it is starting from the specifiedlocation, but the offset is there due to the location of theanti-collision and motion monitoring device 12 in the physical world notlocated at (0,0). In certain embodiments, the calculation for the y-axismay be different than the x-axis due to the fact that the y-offsetstarting point may not necessarily be at the location of theanti-collision and motion monitoring device 12, but rather may be at anoffset a few meters away from the anti-collision and motion monitoringdevice 12. Depending on the location of the anti-collision and motionmonitoring device 12, this may vary in distance. This offset may benoted for the middleware and UI layers.

As described in greater detail herein, in certain embodiments,calibration may be performed for each anti-collision and motionmonitoring device 12 to create a mask of the physical environment 46such that the anti-collision and motion monitoring device 12 may filterout all static objects (e.g., machinery 18) in the physical environment46. In certain embodiments, data relating to such static objects may bestored in memory for analysis. As such, data relating to such staticobjects need not be communicated between anti-collision and motionmonitoring devices 12 and/or the central coordinator 14 during periodsof operation.

In certain embodiments, data packets from the anti-collision and motionmonitoring devices 12 may include a unique identifier (ID) assigned tothe respective anti-collision and motion monitoring device 12 (e.g., amedia access control (MAC) address assigned to the respectiveanti-collision and motion monitoring device 12), a type of object (e.g.,type of machinery 18 or person 20) to which the data packet relates, anX location for the object to which the data packet relates, a Y locationfor the object to which the data packet relates, additional coordinatedata for the object to which the data packet relates, and so forth. Forexample, in certain embodiments, the format of the data packets may be:

[=Start Character

MAC=MAC Address (12-bytes)

;=Data Delimiter (1-byte)

Type=Type of Object (1-byte)

,=Byte Delimiter (1-byte)

X Location=X-Coordinate (1-byte)

,=Byte Delimiter (1-byte)

Y Location=Y-Coordinate (1-byte)

. . . =Additional Coordinates (6-bytes including delimiter)

]=End Character

NULL=NULL Character for End of Bytestream

In certain embodiments, the data elements within the data packets may bestructured such that the data may be read to determine from where thedata is being transmitted and the grid locations of relevant data. Incertain embodiments, each data portion of a data packet may include atotal of 6-bytes including a data delimiter (e.g., semicolon) and bytedelimiters (e.g., commas). In certain embodiments, additional data maybe appended to the data packet after each data delimiter (e.g.,semicolon).

In certain embodiments, the grid (e.g., similar to the rectilinear grid104 illustrated in FIG. 6 ) of the physical environment 46 may beassumed to be completely empty upon initialization and, for example, setto all ‘0’ values. As described in greater detail herein, to minimizedata transmission via the mesh network established by the anti-collisionand motion monitoring devices 12, only relevant data may be transmitted,as opposed to transmitting data relating to the entire grid. Forexample, the anti-collision and motion monitoring devices 12 and themiddleware listeners (e.g., of the central coordinator 14) may only usedata that relates to objects (e.g., machinery 18 and/or people 20) ofinterest so as to avoid network latency.

MAC Address: In certain embodiments, the anti-collision and motionmonitoring devices 12 may transmit the last 4 digits of its unique MACaddress within every data packet. In certain embodiments, the middlewarelistener may maintain this MAC address for all consecutive responses toknow which anti-collision and motion monitoring devices 12 are sendingreceived data. In certain embodiments, the MAC addresses of theanti-collision and motion monitoring devices 12 may be maintained withinmemory until the next reboot, restart, or update.

Object Type: In certain embodiments, the object type included in a datapacket may be represented in a 1-byte hex value table (e.g., relatingdata values with corresponding object types) with many possiblecombinations. In certain embodiments, as described in greater detailherein, the value table may be continually refined as a machine learningmodel is trained and implemented. In certain embodiments, the trainedmachine learning algorithm may be capable of verifying objects atparticular grid locations, and providing information identifying theobject type of the verified objects.

Grid Coordinates: In certain embodiments, the grid coordinates includedin a data packet may be represented by two 2-byte values (e.g., thefirst value being the X coordinate and the next value being the Ycoordinate), which may represent a section of the grid across adedicated area monitored by the specific anti-collision and motionmonitoring device 12. In particular, the two coordinates represent aspecific area in the grid (e.g., similar to the grid sections 106 of therectilinear grid 104 illustrated in FIG. 6 ) where the object type ispresent. In certain embodiments, to minimize data transfer, the locationdata may only be sent if a relevant object (e.g., machinery 18 and/orperson 20) is in the defined space and the grid has the object type fromthe value table described herein. The middleware listener may receivethe type and location information, readily determine to what and wherethe data relates, and provide intelligence needed for a frontend to makedecisions.

To further illustrate how the data packets may be formed, FIG. 7illustrates another view of the rectilinear grid 104 of FIG. 6 . Inparticular, the rectilinear grid 104 illustrated in FIG. 7 includesthree human objects (e.g., having an object type value of 0x1) and onepiece of machinery (e.g., having an object type value of 0x2). Therectilinear grid 104 illustrated in FIG. 7 would look like the followingin packet form:

[00044bc48490;1,7,1;1,3,3,<data element>;2,5,5;1,1,7]

The start characters are designated as brackets, the individual packetdelimiters are designated as semicolons, and the values are separatedwith commas to separate the numbers. The locations are zero indexed. Thedata may be read in the following manner, with <data element>representing data that occurs at the grid section 106 at Row 3, Column3:

[=Start Character

00044bc48490=MAC Address

;=Data Set Delimiter

Data Set 1:

1=Object Type (1)—Human

,=Data Separator

7=Row 7

,=Data Separator

1=Column 1

;=Data Set Delimiter

Data Set 2:

1=Object Type (1)—Human

,=Data Separator

3=Row 3

,=Data Separator

3=Column 3

,=Data Separator

9

8

7

0x1

6

5

0x2

4

3

0x1

2

1

0x1

0

0

1

2

3

4

5

6

7

8

9

;=Data Set Delimiter

Data Set 3:

2=Object Type (2)—Machinery Type #1

,=Data Separator

5=Row 5

,=Data Separator

5=Column 5

;=Data Set Delimiter

Data Set 4:

1=Object Type (1)—Human

,=Data Separator

1=Row 1

,=Data Separator

7=Column 7

]=End Character

In certain embodiments, the interpolated data may be transmitted to themiddleware listener, which expects a data packet containing all therelevant locations of found objects, the middleware listener parses thedata packet and applies the relevant status based on the coordinatelocations of the found objects, and the middleware listener performsintelligence on the data, and lets the UI layer know what it needs todisplay the physical environment 46. In certain embodiments, eachanti-collision and motion monitoring device 12 may wirelessly send itscoordinate packet of the designated data grid. In certain embodiments,the middleware listener may use each of the data packets from aplurality of anti-collision and motion monitoring devices 12 to overlapand triangulate the location of an object based on its individual gridlocation. Using intelligence and the information given, the middlewarelistener will be able to combine all the overlapping grid spaces intoone large area of interest, and place the objects in their correctlocation.

In certain embodiments, the UI layer (e.g., the visualization/UI engine96 of the central coordinator 14) may receive a wrapped data packet fromthe middleware listener to display and configure a user interface 98 toits relevant settings identifying the exact grid locations and relevantareas where potential problems exist. As described in greater detailherein, the user interface 98 allows a user to configure red zones inreal-time, allowing for dynamic operations and zone captures. Thisenables users to be able to switch areas of interest quickly andefficiently. FIGS. 8-11 illustrate a plurality of views that may bedisplayed via the user interface 98, depicting how the grid and itsassociated objects may be displayed. In particular, FIG. 11 illustratesa view having an alert displayed when a potential problem exists.

In addition, in certain embodiments, the visualization/UI engine 96 mayalso be configured to provide, among other things, a user interface 98that displays a grid heat map of the physical environment 46 beingmonitored by the anti-collision and motion control system 10. Forexample, FIG. 6 also illustrates an example of a “heat map” for aphysical environment 46 being monitored by the anti-collision and motioncontrol system 10. For example, as illustrated in FIG. 6 , in certainembodiments, certain grid sections 106 may depict regions 112 that haveparticularly high levels of movement or other activity, such as heat andnoise, in them (i.e., “hot zones”). In certain embodiments, regions 112may be identified by color to illustrate the degree of movement and/orother activity that these regions 112 tend to have. For example, regions112 with relatively high levels movement and/or other activity may becolored red, whereas regions 112 with relatively low levels movementand/or other activity may be colored green (or have no color at all),and the regions 112 with levels of movement and/or other activity inbetween may vary across an appropriate spectrum between red and green(or no color at all). The heat map illustrated in FIG. 6 may, forexample, enable users to redesign processes performed in the physicalenvironment 46.

In certain embodiments, data science algorithms may be implementedusing, for example, neural networks to create a machine learning modelfor the object classification performed by the object classificationmodules 66 of the anti-collision and motion monitoring devices 12. Incertain embodiments, the algorithms may be continuously re-trained anditerated to yield the most accurate results in identifying humans vs.machinery, certain types of machinery from each other, and so forth. Incertain embodiments, custom neural networks may be created to classifybase images from, for example, a public data set. In other embodiments,pre-trained models may be pre-trained based on images from environmentssimilar to the physical environment 46 being monitored (e.g., images forother drill rings when a drill rig is being monitored). In yet otherembodiments, knowledge learned from existing models may be customized tothe particular criteria of the physical environment 46 being monitored.In such embodiments, cropping and fixation may be used to locate areasof interest in images, cropping the areas of interest to smallersubsections, and sizing them for the model.

As described in greater detail herein, the anti-collision and motioncontrol system 10 may be configured to alert people 20 located in thephysical environment being monitored by the one or more anti-collisionand motion monitoring devices 12, for example, when the people 20 moveinto areas of the physical environment that the central coordinator 14believes that the people 20 should not be. In particular, in certainembodiments, the anti-collision and motion control system 10 may trackthe number of people 20 in particular zones (e.g., in hot zones, asdepicted by the grid sections 112 in FIG. 6 ), how long the people 20have been in the particular zones, operational activity of machinery 18in the particular zones, and so forth, may access current operatingparameters of the machinery 18, and may use all of this data todetermine when alerts should be generated (e.g., without humanintervention, in certain embodiments). For example, in certainembodiments, the anti-collision and motion control system 10 maygenerate an alert when a certain threshold of people 20 in a particularhot zone is exceeded. The alerts that may be generated may includevisual alarms (e.g., visual messages, color changes, changes in textsize, and so forth) that are displayed via a user interface 98, auditoryalarms (e.g., different audio tones for different people 20, and soforth) that are created via a user interface 98, and any other suitablealarms.

As illustrated in FIGS. 2 and 5 , in certain embodiments, theanti-collision and motion control system 10 may also generate alarms viacertain wearable devices 114 associated with certain people 20 (e.g.,without human intervention, in certain embodiments). For example, incertain embodiments, a person 20 may be assigned a helmet (e.g.,hardhat) 114A, a badge 114B, a glove or pair of gloves 114C, a belt114D, a boot or pair of boots 114E, and/or any other wearable devices114 (e.g., embedded in or attached to other types of clothing and gear,such as hats, glasses, coats, jackets, shirts, vests, pants, shoes,tools, and so forth), which may have processing circuitry 116 embeddedtherein, or otherwise attached thereto, that is configured to generatecertain alarms based on alarm signals received, for example, from thecentral coordinator 14 of the anti-collision and motion control system10 via wireless communication circuitry 118 of the wearable devices 114.For example, the processing circuitry 116 of the wearable devices 114may include at least one processor 120, at least one memory medium 122,at least one actuator 124, or any of a variety of other components thatenable the processing circuitry 116 to carry out the techniquesdescribed herein.

In particular, the at least one processor 120 of the wearable devices114 may be configured to use alarm signals received, for example, fromthe central coordinator 14 of the anti-collision and motion controlsystem 10 via the communication circuitry 118 of the wearable devices114, and to execute instructions stored in the at least one memorymedium 122 of the wearable devices 114 to cause the at least oneactuator 124 of the wearable devices 114 to generate an alarm, such ashaptic feedback, audible sounds, or some combination thereof, inaccordance with the received alarm signals. In addition, in certainembodiments, the wearable devices 114 may be augmented reality googlesor glasses configured to display certain alarms via at least oneaugmented reality display 126 of the wearable devices 114.

In addition, in certain embodiments, the wearable devices 114 may alsoinclude markers 128, such as reflective materials and/or markers havingspecific recognizable shapes or patterns, that may be detected by theanti-collision and motion monitoring devices 12 described herein to aidin the tracking of movement and/or orientation of the wearable devices114 and, by extension, the people 20 who are assigned to the wearabledevices 114. Indeed, in certain embodiments, some pieces of machinery 18may also have such markers 128 attached thereto, which may similarly bedetected by the anti-collision and motion monitoring devices 12described herein to aid in the tracking of movement and/or orientationof the pieces of machinery 18. In addition, in certain embodiments, thewearable devices 114 may also include a battery 130 to provide therespective wearable device 114 with power.

The at least one processor 120 of the wearable devices 114 may be anysuitable type of computer processor or microprocessor capable ofexecuting computer-executable code. In certain embodiments, the at leastone processor 120 of the wearable devices 114 may also include multipleprocessors that may perform the operations described herein. The atleast one memory medium 122 of the wearable devices 114 may be anysuitable articles of manufacture that can serve as media to storeprocessor-executable code, data, or the like. These articles ofmanufacture may represent computer-readable media (e.g., any suitableform of memory or storage) that may store the processor-executable codeused by the at least one processor 120 to perform the presentlydisclosed techniques. As described in greater detail herein, the atleast one memory medium 122 of the wearable devices 114 may also be usedto store data, various other software applications, and the like. The atleast one memory medium 122 of the wearable devices 114 may representnon-transitory computer-readable media (e.g., any suitable form ofmemory or storage) that may store the processor-executable code used bythe at least one processor 120 to perform various techniques describedherein. It should be noted that non-transitory merely indicates that themedia is tangible and not a signal. In certain embodiments, the at leastone actuator 124 of the wearable devices 114 may include any actuatorsthat are configured to generate alarms, such as haptic feedback devicesconfigured to vibrate or otherwise move, speakers configured to generateaudible sounds, or some combination thereof.

The types of alarms that may be generated by the actuators 124 of thewearable devices 114 may vary based upon the particular operations ofthe wearable devices 114. For example, in certain embodiments, as aperson 20 moves closer to a piece of machinery 18 that is considered tobe in a hot zone, haptic feedback generated by an actuator 124 of awearable device 114 being worn by the person 20 may intensify and/oraudible sounds generated by the actuator 124 of the wearable device 114being worn by the person 20 may grow louder. In other embodiments, thetype of haptic feedback and/or audible sounds generated by the actuators124 of the wearable devices 114 may vary based on a type of alarm. Forexample, a first type of alarm (e.g., a notification of proximity of aperson 20 to a particular piece of machinery 18) may generate aparticular pattern of haptic vibrations and/or audible sounds, whereas asecond type of alarm (e.g., a notification to evacuate the particularphysical environment 46) may generate a different pattern of hapticvibrations and/or audible sounds. In other embodiments, the type ofhaptic feedback and/or audible sounds generated by the actuators 124 ofthe wearable devices 114 may vary based on a type of machinery 18 towhich a person 20 is getting closer and/or to the relative level ofmovement and/or other activity that tends to occur in a particularregion (e.g., whether categorized as a hot zone or not) of the physicalenvironment 46 to which a person 20 is getting closer.

In certain embodiments, the alarms may not only be generated by theanti-collision and motion control system 10 via wearable devices 114that are being worn by the person 20 to which the alarm relates, butalso to other people 20, such as supervisors and/or operators of themachinery 18. For example, if a first person 20 is getting to close to aparticular piece of machinery 18 and/or a particular region of thephysical environment 46, the first person 20 as well as a second person20 (e.g., a supervisor and/or an operator of the machinery 18) may bothbe alerted by the anti-collision and motion control system 10 viarespective wearable devices 114 (e.g., without human intervention, incertain embodiments).

While only certain features have been illustrated and described herein,many modifications and changes will occur to those skilled in the art.It is, therefore, to be understood that the appended claims are intendedto cover all such modifications and changes as fall within the truespirit of the disclosure.

The techniques presented and claimed herein are referenced and appliedto material objects and concrete examples of a practical nature thatdemonstrably improve the present technical field and, as such, are notabstract, intangible or purely theoretical. Further, if any claimsappended to the end of this specification contain one or more elementsdesignated as “means for [perform]ing [a function] . . . ” or “step for[perform]ing [a function] . . . ”, it is intended that such elements areto be interpreted under 35 U.S.C. § 112(f). However, for any claimscontaining elements designated in any other manner, it is intended thatsuch elements are not to be interpreted under 35 U.S.C. § 112(f).

The invention claimed is:
 1. An anti-collision and motion controlsystem, comprising: a plurality of anti-collision and motion monitoringsystems, each anti-collision and motion monitoring system beingpositioned at a different stationary position in an environment andcomprising: one or more light detection and ranging (LiDAR) systemsconfigured to detect locations of one or more objects in theenvironment; one or more camera systems configured to capture images ofthe one or more objects in the environment that are detected by the oneor more LiDAR systems; and processing circuitry configured to receiveinputs from the one or more LiDAR systems and the one or more camerasystems relating to the one or more objects in the environment, and toprocess the inputs received from the one or more LiDAR systems and theone or more camera systems to determine outputs relating to the one ormore objects in the environment; and a central coordinator configured toreceive the outputs from the processing circuitry of the plurality ofanti-collision and motion monitoring systems, to compile the outputsinto visualization data relative to a plurality of grid sections of arectilinear grid of the environment, and to communicate a visualizationof the rectilinear grid of the environment to a user interface, whereinthe visualization comprises the visualization data relative to theplurality of grid sections of the rectilinear grid of the environment,wherein the visualization data defines positioning and movement of theone or more objects relative to the plurality of grid sections of therectilinear grid of the environment, and wherein the visualization ofthe rectilinear grid of the environment includes a heat map providingvisual indication of a relative level of movement within each of thegrid sections.
 2. The anti-collision and motion control system of claim1, wherein the central coordinator is configured to receive the outputsfrom the processing circuitry of the plurality of anti-collision andmotion monitoring systems as data formatted in a data formatcorresponding to the plurality of grid sections of the rectilinear gridof the environment.
 3. The anti-collision and motion control system ofclaim 1, wherein the central coordinator is configured to determine oneor more alarms relating to activity of the one or more objects in theenvironment based at least in part on the outputs received from theprocessing circuitry of the plurality of anti-collision and motionmonitoring systems, and to communicate the one or more alarms to theuser interface via the visualization of the rectilinear grid of theenvironment.
 4. The anti-collision and motion control system of claim 1,wherein the central coordinator is configured to determine one or morealarms relating to activity of the one or more objects in theenvironment based at least in part on the outputs received from theprocessing circuitry of the plurality of anti-collision and motionmonitoring systems, and to communicate the one or more alarms to one ormore wearable devices located in the environment.
 5. The anti-collisionand motion control system of claim 1, wherein the central coordinator isconfigured to control one or more operating parameters of at least oneof the one or more objects in the environment based at least in part onthe outputs received from the processing circuitry of the plurality ofanti-collision and motion monitoring systems.
 6. An anti-collision andmotion monitoring system, comprising: a housing configured forstationary positioning in an environment: one or more light detectionand ranging (LiDAR) systems configured to detect locations of one ormore objects in an environment in the housing; one or more camerasystems configured to capture images of the one or more objects in theenvironment that are detected by the one or more LiDAR systems in thehousing; processing circuitry in the housing configured to receiveinputs from the one or more LiDAR systems and the one or more camerasystems relating to the one or more objects in the environment, toprocess the inputs received from the one or more LiDAR systems and theone or more camera systems to determine primary data relating to the oneor more objects in the environment relative to a first plurality of gridsections of a rectilinear grid of the environment, and to requestcomplementary data relating to the one or more objects in theenvironment relative to a second plurality of grid sections of therectilinear grid from a second anti-collision and motion monitoringsystem only when the processing circuitry cannot determine primary datarelating to the one or more objects in the environment relative to thesecond plurality of grid sections of the rectilinear grid; and a centralcoordinator configured to compile the primary data and the requestedcomplementary data from the processing circuitry into a visualization ofthe rectilinear grid, the visualization comprising a heat map thatprovides visual indication of a relative level of movement within eachof the grid sections.
 7. The anti-collision and motion monitoring systemof claim 6, wherein the processing circuitry is configured to formatoutputs relating to the primary data and the complementary data into adata format corresponding to the first and second pluralities of gridsections of the rectilinear grid of the environment, and to communicatethe outputs to the central coordinator.
 8. The anti-collision and motionmonitoring system of claim 6, wherein the processing circuitry isconfigured to request the complementary data relating to the one or moreobjects in the environment relative to the second plurality of gridsections of the rectilinear grid from the second anti-collision andmotion monitoring system only when the one or more LiDAR systems or theone or more camera systems do not have line of sight of at least one ofthe one or more objects in the environment.
 9. The anti-collision andmotion monitoring system of claim 8, wherein the processing circuitry isconfigured to request the complementary data relating to the one or moreobjects in the environment relative to the second plurality of gridsections of the rectilinear grid from the second anti-collision andmotion monitoring system only when the at least one of the one or moreobjects in the environment is determined to be in a zone of interestwithin the environment.
 10. The anti-collision and motion monitoringsystem of claim 8, wherein the processing circuitry is configured toselect the second anti-collision and motion monitoring system from aplurality of anti-collision and motion monitoring systems in theenvironment based at least in part on a relative proximity to the secondanti-collision and motion monitoring system as compared to otheranti-collision and motion monitoring systems of the plurality ofanti-collision and motion monitoring systems.
 11. The anti-collision andmotion monitoring system of claim 8, wherein the processing circuitry isconfigured to select the second anti-collision and motion monitoringsystem from a plurality of anti-collision and motion monitoring systemsin the environment based at least in part on a confidence level that thesecond anti-collision and motion monitoring system can provide thecomplementary data relating to the one or more objects in theenvironment.
 12. The anti-collision and motion monitoring system ofclaim 8, wherein the processing circuitry is configured to select thesecond anti-collision and motion monitoring system from a plurality ofanti-collision and motion monitoring systems in the environment based atleast in part on a relative signal strength from the secondanti-collision and motion monitoring system as compared to otheranti-collision and motion monitoring systems of the plurality ofanti-collision and motion monitoring systems.
 13. An anti-collision andmotion control system, comprising: one or more anti-collision and motionmonitoring systems, each anti-collision and motion monitoring systembeing configured for stationary positioning in an environment andcomprising: one or more light detection and ranging (LiDAR) systemsconfigured to detect locations of one or more objects in theenvironment; one or more camera systems configured to capture images ofthe one or more objects in the environment that are detected by the oneor more LiDAR systems; and processing circuitry configured to receiveinputs from the one or more LiDAR systems and the one or more camerasystems relating to the one or more objects in the environment, and toprocess the inputs received from the one or more LiDAR systems and theone or more camera systems to determine outputs relating to the one ormore objects in the environment; and a central coordinator configured toreceive the outputs from the processing circuitry of the one or moreanti-collision and motion monitoring systems, to determine one or morealarms relating to activity of the one or more objects in theenvironment based at least in part on the outputs received from theprocessing circuitry of the one or more anti-collision and motionmonitoring systems, and to communicate the one or more alarms to one ormore wearable devices located in the environment, wherein the centralcoordinator is configured to compile the outputs into visualizationdata, the visualization data defining a visualization of a rectilineargrid of the environment, the visualization comprising a heat map thatprovides visual indication of a relative level of movement within eachgrid section in the rectilinear grid.
 14. The anti-collision and motioncontrol system of claim 13, wherein the one or more wearable devicescomprise a helmet.
 15. The anti-collision and motion control system ofclaim 13, wherein the one or more wearable devices comprise a badge. 16.The anti-collision and motion control system of claim 13, wherein theone or more wearable devices comprise a glove.
 17. The anti-collisionand motion control system of claim 13, wherein the one or more wearabledevices comprise a belt.
 18. The anti-collision and motion controlsystem of claim 13, wherein the one or more wearable devices comprise aboot.
 19. The anti-collision and motion control system of claim 13,wherein the one or more wearable devices comprise augmented realityglasses or augmented reality goggles configured to display the one ormore alarms via an augmented reality display of the augmented realityglasses or augmented reality goggles.